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‍Enhanced remote sensing ecological index and ecological environment evaluation in arid area

  • role： First author第一作者
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

    Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, Nanjing 210023, China

    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China

  • Email：zhangwrs@163.com
  • Introduction：张伟，研究方向为遥感影像处理与时序分析。E-mail： zhangwrs@163.com
ZHANG Wei123,  
  • role： Corresponding author通信作者
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

    Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, Nanjing 210023, China

    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China

  • Email：peijun@nju.edu.cn
  • Introduction：杜培军，研究方向为城市环境遥感。E-mail： peijun@nju.edu.cn
DU Peijun123*,  
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

    Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, Nanjing 210023, China

    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China

GUO Shanchuan123,  
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

    Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, Nanjing 210023, China

    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China

LIN Cong123,  
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

    Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, Nanjing 210023, China

    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China

ZHENG Hongrui123,  
  • Affiliation：

    School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China.

FU Pingjie4

реферат

Long-term, quantitative and dynamic monitoring of large-scale regional ecological environmental quality using remote sensing images can provide strong decision support for regional sustainable development. Based on the Remote Sensing based Ecological Index (RSEI), an enhanced Remote Sensing Ecological Index (ERSEI) is proposed from the perspective of the elements of the coupled ecosystem considering regional characteristics and application requirements of the ecological environment in arid areas. The ERSEI considers the factors of greenness (NDVI), wetness (Wet), dryness (NDBSI), and heat (LST) while introducing the Comprehensive Salinity Index (CSI) and estimation model of water network density (EMW). The salinity and Water Network Density (WND) are included in the ecological environment quality assessment. With the help of the Google Earth Engine (GEE) cloud computing platform, ERSEI is applied to the Hohhot-Baotou-Ordos-Yulin urban agglomeration in the arid area of northwestern China. The results show that the ERSEI can fully reflect the detailed characteristics of the surface in arid areas and effectively highligh the gradual information of the radiation impact of the water network on the surrounding environment. According to the spatial measurement and time series evolution analysis of ERSEI in the Hohhot-Baotou-Ordos-Yulin urban agglomeration from 2000 to 2020, it is found that areas with good ecological environment quality are mainly distributed in the Hetao Plain, Daqing Mountain and the side close to Luliang Mountain. Areas with poor ecological environment quality are mainly concentrated in the Mongolian Plateau, near the Hobq Desert and the Mu Us Sandy Land, and the quality of the ecological environment has shown a continuous decline. Therefore, these areas should be treated as ecological risk early warning zones to strengthen governance. The ERSEI provides a fast and effective new method for the normalized monitoring of ecological environment quality in arid areas.

ключеви́че слова́

ERSEI;spatial measurement of ecological environment;time series evolution analysis;Google Earth Engine;Hohhot-Baotou-Ordos-Yulin urban agglomeration;ecological risk warning zone

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